Senior Deep Learning Scientist – Multimodal Agentic RL

NVIDIA

Senior Deep Learning Scientist advancing multimodal AI at NVIDIA. Focusing on deep learning, RL, and applied mathematics on high-impact AI products.

Posted 7/25/2026full-timeSanta Clara • California • 🇺🇸 United StatesSenior💰 $184,000 - $287,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Expertise in developing and deploying advanced neural networks for language processing, with a strong focus on multimodal models and reinforcement learning techniques. Proven ability to manage the model development life cycle and ensure high-quality evaluation of model performance.

Highest-signal resume keywords

Python ProgrammingDeep Learning FrameworksMultimodal Model DevelopmentReinforcement Learning AlgorithmsModel Development Life Cycle Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Neural Network DevelopmentDeep LearningMachine Learning TechniquesTransformersMixture-of-Experts ModelsInstruction TuningPreference OptimizationAudio-Visual ReasoningDataset VersioningExperiment Tracking

Tools & Technologies

PyTorch

Industry Keywords

Agentic SystemsGrounded PerceptionPlanningTool ExecutionLong-Horizon Task CompletionModel AccuracySafety EvaluationTask Completion Success

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

Apply fundamental and applied research to develop, train, fine-tune, and deploy advanced neural networks for language processing in agentic systems encompassing audio-visual reasoning, tool usage, and document understanding
Advance post-training and alignment methods including instruction tuning, preference optimization, and RLHF/RLVR to improve multimodal agents for complex use cases
Research and develop agentic reasoning and grounded perception capabilities, focusing on planning, tool execution, and long-horizon task completion across digital and physical environments
Lead the collection, development, and benchmarking of multimodal datasets, ensuring high-quality evaluation of model accuracy, safety, and task completion success

Requirements

What you’ll need

Master’s degree (or equivalent experience) or PhD in Computer Science, AI, or Applied Math with 8+ years of relevant work experience
Excellent programming skills in Python with strong fundamentals in scalable model development and deep learning frameworks like PyTorch
Strong knowledge of ML/DL techniques and modern foundation model architectures, including Transformers and mixture-of-experts models
Foundational understanding of reinforcement learning algorithms and implementation, including MDPs, policies, and reward design
Hands-on experience in post-training multimodal models for audio-visual reasoning and human-AI interaction
Proven ability to manage model development life cycles, including dataset versioning, experiment tracking, and evaluation pipelines

Benefits

Comp & perks

Highly competitive salaries
Comprehensive benefits package
Equity opportunities